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Python developer quant data - hedge fund

London
Millennium Management
Python developer
Posted: 2 July
Offer description

Quantitative Developer - Python Millennium is a top tier global hedge fund with a strong commitment to leveraging innovations in technology and data science to solve complex problems for the business.
Risk Technology team is looking for a Quantitative Developer who would leverage Python, Cloud infrastructure (AWS), and scientific frameworks to provide data-driven, risk management solutions to Risk Managers, Portfolio Managers, Business Management.
Responsibilities:
· Work in the intersection of Portfolio Management, Risk Management and Quantitative Research to develop risk analytics solutions for Equity Derivatives businesses.
· Collaborate with risk management for rapid prototyping and delivery of solutions to enhancement risk metrics.
· Develop data ingestion pipelines and analytics the generated information.
· Design and implement cloud-native, data-intensive applications that effectively leverage AWS solutions
· Mentor junior team members, fostering growth and collaboration within the team.
· Fit into the active culture of Millennium, judged by the ability to deliver timely solutions to Portfolio and Risk Managers
Required Skills/Experience:
· Minimum 5 years of experience using Python and scientific python libraries (e.g., pandas, NumpPy, SciPy).
· Strong understanding of cloud infrastructure and experience working with cloud services (e.g., AWS, Azure, or GCP).
· Prior experience in system design and data modeling, with the ability to architect scalable and efficient solutions for trading, risk management or similar functions.
· Strong analytical and mathematical skills, with interest and exposure to quantitative finance and equity derivative products (desirable)
· Relational database development experience, with a focus on designing efficient schemas and optimizing queries.
· Unix/Linux command-line experience.
· Ability to work independently in a fast-paced environment.
· Detail-oriented, organized, demonstrating thoroughness and strong ownership of work.
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